Antibiotics and hospital-acquired Clostridium difficile infection: update of systematic review and meta-analysis
Bibliographic record
Abstract
OBJECTIVES: To update the evidence for associations between antibiotic classes and hospital-acquired Clostridium difficile infection (HA-CDI). METHODS: Electronic databases of journal articles, scholarly theses and conference proceedings using subject headings and keywords related to CDI and antibiotic exposure were searched. Observational epidemiological studies measuring associations between antibiotic classes and HA-CDI were eligible for inclusion. Pooled ORs and 95% CIs were calculated using a random effects model. Study factors identified a priori were examined as sources of heterogeneity. The quality of the studies was assessed using the Newcastle-Ottawa Scale. RESULTS: Of 569 citations identified, 13 case-control and 1 cohort study (15,938 patients) were included. The strongest associations were found for third-generation cephalosporins (OR = 3.20, 95% CI = 1.80-5.71; n = 6 studies; I(2) = 79.2%), clindamycin (2.86, 2.04-4.02; n = 6; I(2) = 28.5%), second-generation cephalosporins (2.23, 1.47-3.37; n = 6; I(2) = 48.4%), fourth-generation cephalosporins (2.14, 1.30-3.52; n = 2; I(2) = 0.0%), carbapenems (1.84, 1.26-2.68; n = 6; I(2) = 0.0%), trimethoprim/sulphonamides (1.78, 1.04-3.05; n = 5; I(2) = 70%), fluoroquinolones (1.66, 1.17-2.35; n = 10; I(2) = 64%) and penicillin combinations (1.45, 1.05-2.02; n = 6; I(2) = 54%). The study population and the timing of measurement of antibiotic exposure were the most common sources of heterogeneity. Study quality scored high for seven studies, moderate for six studies and low for one study. CONCLUSIONS: The risk of HA-CDI remains greatest for cephalosporins and clindamycin, and their importance as inciting agents should not be minimized. The importance of fluoroquinolones should not be overemphasized, particularly if fluoroquinolone-resistant epidemic strains of C. difficile are absent.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.041 | 0.099 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.028 |
| Bibliometrics | 0.015 | 0.014 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".